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Dynamic evolution process of financial impact path under the multidimensional spatial effect based on G20 financial network

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  • Zhang, Weiping
  • Zhuang, Xintian
  • Li, Yanshuang

Abstract

This paper describes the features of the multidimensional spatial effects among G20 financial markets and investigates the dynamic evolution process of financial impact in the spatial spillover networks. To achieve this objective, we first define the economic metric and gravitational spatial weight matrix to establish a multidimensional economic space, which is shown to have a significant advantage in capturing the multidimensional spatial effects of financial markets. Then, the spatial econometric complex network autoregressive panel model is constructed by combining the spatial econometrics and complex network theory. Finally, we calculate the Bonacich centrality of nodes in spillover network, and study dynamic process of the financial impact path with different Bonacich nodes being the source of infection. The results show that spatial spillover network includes regional aggregation and dynamic evolution. The spatial spillover effects of financial markets are positively correlated with important financial markets, foreign direct investment, turnover ratio and inflation rate. Emerging financial markets are seen to have increasingly become Bonacich key nodes in the impact path. When the Bonacich key nodes in the spillover network have fluctuations, the impact spreads wider and faster. This study can help us predict the source of the financial turmoil, and remind investors to formulate new asset allocation strategies and risk prevention measures for different financial markets.

Suggested Citation

  • Zhang, Weiping & Zhuang, Xintian & Li, Yanshuang, 2019. "Dynamic evolution process of financial impact path under the multidimensional spatial effect based on G20 financial network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    • Handle: RePEc:eee:phsmap:v:532:y:2019:i:c:s0378437119311057
    DOI: 10.1016/j.physa.2019.121876
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    Citations

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    Cited by:

    1. Shaowei Chen & Long Guo & Weike Zhang, 2023. "Financial Risk Measurement and Spatial Spillover Effects Based on an Imported Financial Risk Network: Evidence from Countries along the Belt and Road," Mathematics, MDPI, vol. 11(6), pages 1-25, March.
    2. Li, Yanshuang & Zhuang, Xintian & Wang, Jian & Dong, Zibing, 2021. "Analysis of the impact of COVID-19 pandemic on G20 stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    3. Wen, Tiange & Wang, Gang-Jin, 2020. "Volatility connectedness in global foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 54(C).
    4. Fu Qiao & Yan Yan, 2020. "How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19," Papers 2007.07487, arXiv.org.
    5. Su, Zhi & Xu, Fuwei, 2021. "Dynamic identification of systemically important financial markets in the spread of contagion: A ripple network based collective spillover effect approach," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    6. Nan, Shijing & Wang, Minna & You, Wanhai & Guo, Yawei, 2023. "Making text count: Identifying systemic risk spillover channels in the Chinese banking sector using annual reports text," Finance Research Letters, Elsevier, vol. 55(PA).
    7. Li, Yanshuang & Zhuang, Xintian & Wang, Jian, 2021. "Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

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